Software as a service (SaaS) is a primary working pattern and a significant application model for next generation Internet application. Web GIS services are the new generation of the Software as a service that can provide the hosted spatial data and GIS functionalities to the practical customized applications. This study focused on developing a webGIS based application, Soil Moisture-Based Irrigation Scheduling Tool (SMIST), for predicting soil moisture in the next seven days using the soil moisture diagnostic equation (SMDE) and the upcoming seven precipitation forecasts made by the National Weather Service (NWS), and ultimately producing an accurate irrigation schedule based on the predicted soil moisture. The SMIST is expected to be capable of improving the irrigation efficiency to protect groundwater resources in the Texas High Plains and reducing the cost of energy for pumping groundwater for irrigation, as an essential public concern in this area. The SMIST comprised an integration of web-based programs, a Hydrometeorological model, GIS, and geodatabase. It integrates two main web systems, the soil moisture estimating web application for irrigation scheduling based on the soil moisture diagnostic equation (SMDE), and an agricultural field delineation webGIS application to prepare input data and the model parameters. The SMIST takes advantage of the latest historical and forecasted precipitation data to predict soil moisture in the user-specified agricultural field(s). In this regard, the next seven days soil moisture versus the soil moisture threshold for normal growth would be presented in the result page of the SMIST to help users to adjust irrigation rate and sequence.

Les épisodes de sécheresse et de canicule qui frappent épisodiquement les régions tempérées ont des conséquences préjudiciables sur les plans sanitaire, économique, social et écologique. Afin de pouvoir enclencher des stratégies de préparation et de prévention avec quelques semaines ou mois d'anticipation, les attentes sociétales en matière de prévision sont élevées, et ce d'autant plus que les projections climatiques font craindre la multiplication de ces épisodes au cours du 21ème siècle. Néanmoins, la saison d'été est la plus difficile à prévoir aux moyennes latitudes. Les sources connues de prévisibilité sont plus ténues qu'en hiver et les systèmes de prévision climatique actuels peinent à représenter correctement les mécanismes de téléconnexion associés. Un nombre croissant d'études a mis en évidence un lien statistique dans certaines régions entre l'humidité du sol au printemps et les températures et précipitations de l'été qui suit. Ce lien a été partiellement confirmé dans des modèles numériques de climat mais de nombreuses interrogations subsistent. L'objectif de cette thèse est donc de mieux comprendre le rôle joué par l'humidité du sol sur les caractéristiques et la prévisibilité du climat de l'été dans les régions tempérées. Grâce notamment au modèle couplé de circulation générale CNRM-CM, nous avons mis en œuvre des ensembles de simulations numériques qui nous ont permis d'évaluer le degré de persistance des anomalies d'humidité du sol printanière. En effet, une longue persistance est une condition nécessaire pour que ces anomalies influencent le climat à l'échelle de la saison, via le processus d'évapotranspiration de la surface. En imposant dans notre modèle des conditions initiales et aux limitées idéalisées d'humidité du sol, nous avons mis en évidence des régions du globe pour lesquelles l'état moyen et la variabilité des températures et des précipitations en été sont particulièrement sensibles à ces conditions. C'est notamment le cas sur une grande partie de l'Europe et de l'Amérique du nord, y compris à des latitudes élevées. Pour toutes ces régions, l'humidité du sol est une source prometteuse de prévisibilité potentielle du climat à l'horizon saisonnier, bien que de fortes incertitudes demeurent localement sur le degré de persistance de ses anomalies. Une expérience de prévisibilité effective coordonnée avec plusieurs systèmes de prévision montre qu'une initialisation réaliste de l'humidité du sol améliore la prévision de températures estivales principalement dans le sud-est de l'Europe. Dans d'autres régions, comme l'Europe du Nord, le désaccord des modèles provient de l'incertitude sur la persistance des anomalies d'humidité du sol. En revanche, sur les Grandes Plaines américaines, aucun modèle n'améliore ses prévisions qui restent donc très médiocres. La littérature ainsi que nos évaluations de sensibilité du climat à l'humidité du sol ont pourtant identifié cette région comme un "hotspot" du couplage entre l'humidité du sol et l'atmosphère. Nous supposons que l'échec de ces prévisions est une conséquence des forts biais chauds et secs présents dans tous les modèles sur cette région en été, qui conduisent à un dessèchement excessif des sols. Pour le vérifier, nous avons développé une méthode qui corrige ces biais au cours de l'intégration des prévisions avec CNRM-CM6. Les prévisions qui en résultent sont nettement améliorées sur les Grandes Plaines. La compréhension de l'origine des biais continentaux en été et leur réduction dans les prochaines générations de modèles de climat sont des étapes essentielles pour tirer le meilleur parti de l'humidité du sol comme source de prévisibilité saisonnière dans les régions tempérées. / Severe heat waves and droughts that episodically hit temperate regions have detrimental consequences on health, economy and society. The design and deployment of efficient preparedness strategies foster high expectations for the prediction of such events a few weeks or months ahead. Their likely increased frequency throughout the 21st century, as envisaged by climate projections, further emphasizes these expectations. Nevertheless, the summer season is the most difficult to predict over mid-latitudes. Well-known sources of predictability are weaker than in winter and current climate prediction systems struggle to adequately represent associated teleconnection mechanisms. An increasing number of studies have shown a statistical link over some regions between spring soil moisture and subsequent summer temperature and precipitation. This link has been partly confirmed in climate numerical models, but many questions remain. The purpose of this PhD thesis is to better understand the role played by soil moisture onthe characteristics and predictability of the summer climate in temperate regions. By means of the CNRM-CM coupled general circulation model, we have designed a range of numerical simulations which help us evaluate the persistence level of spring soil moisture anomalies. Indeed, a long persistence is a necessary condition for these anomalies to influence the climate at the seasonal scale, through the process of evapotranspiration. By imposing in our model idealized initial and boundary soil moisture conditions, we have highlighted areas of the globe for which the average state and the variability of temperatures and precipitation in summer is particularly sensitive to these conditions. This is the case in particular for Europe and North America, including over high latitudes. Soil moisture is therefore a promising source of potential seasonal climate predictability for these regions, although the persistence of soil moisture anomalies remains locally very uncertain. An effective predictability coordinated experiment, bringing together several prediction systems, shows that a realistic soil moisture initialization improves the forecast skill of summer temperatures mainly over southeast Europe. In other regions, such as Northern Europe, the disagreement between models comes from uncertainty about the persistence of soil moisture anomalies. On the other hand, over the American Great Plains, even the forecasts with improved soil moisture initialization remain unsuccessful. Yet, the literature as well as our assessment of climate sensitivity to soil moisture have identified this region as a "hotspot" of soil moisture - atmosphere coupling. We assume that the failure of these predictions relates to the strong hot and dry bias present in all models over this region in summer, which leads to excessive soil drying. To verify this assumption, we developed a method that corrects these biases during the forecast integration based on the CNRM-CM6 model. The resulting forecasts are significantly improved over the Great Plains. Understanding the origin of continental biases in the summer and reducing them in future generations of climate models are essential steps to making the most of soil moisture as a source of seasonal predictability in temperate regions

Irrigated agriculture is the largest user of freshwater in a world experiencing increased water scarcity and water demands. Variable rate irrigation (VRI) aims to use water efficiently in crop production, resulting in good yields and water conservation. With VRI, the grower is able to employ custom irrigation rates for different parts of a field. Adoption of VRI has been limited due to the complexity of matching irrigation to spatiotemporal crop water needs and the cost/benefit economics of VRI equipment. The goal of this study was to quantify spatiotemporal variability of VWC in a field that has uniform soil type and discuss the driving factors that contribute to that variability. Soil samples were acquired at 66 and 87 locations during the 2019 growing season at two study sites. Soil samples from 32 and 48 locations within each study site were selected to be analyzed for soil texture properties. The USGS Web Soil Survey was also referenced. Both, the USGS data and the data collected for this project showed very uniform soils across both fields. The objectives of this study were i) to show variability of VWC within fields that contain uniform soil texture using univariate Local Moran’s I (LMI) and ii) to compare static VRI zones based on spatial patterns of readily available field data that might serve as surrogates for VRI zones created from measured variation of soil volumetric water content (VWC). Management zones created using readily available field data had reasonable correlations with VWC. In both study sites, elevation was found to be the best variable for delineating VRI zones that imitate measured VWC.

The main goal of this research is to quantitatively assess the resilience and vulnerability of geotechnical infrastructure to extreme events under a changing climate. In the first part, pertinent facts and statistics regarding California’s extreme drought and current status of its levees are presented. Weakening processes such as soil strength reduction, soil desiccation cracking, land subsidence and surface erosion, and oxidation of soil organic carbon are comprehensively evaluated to illustrate the devastating impacts that the California drought can have on earthen structures. In the second part, rainfall-triggered slope instabilities are analyzed using extreme precipitation estimates, derived using the historical stationary and a proposed future nonstationary approach. The extremes are integrated into a series of fully coupled 2D finite element simulations. The final part of this study investigates the impact of simultaneous variations in soil moisture and temperature changes in the California region on soil strength through a proposed thermo-hydro-mechanical framework.

A three-dimensional computational tool was developed that simulates the heat and mass transfer interaction in a soil-root-stem system (SRSS) for a tree in a seasonally varying deciduous forest. The development of the SRSS model involved the modification and coupling of existing heat and mass transport tools to reproduce the three-dimensional diurnal internal and external temperatures, internal fluid distribution, and heat flow in the soil, roots, and stems. The model also required the development of a parallel Monte-Carlo algorithm to simulate the solar and environmental radiation regime consisting of sky and forest radiative effects surrounding the tree. The SRSS was tested, component-wise verified, and quantitatively compared with published observations. The SRSS was applied to simulate a tree in a dense temperate hardwood forest that included the calculations of surface heat flux and comparisons between cases with fluid flow transport and periods of zero flow. Results from the winter simulations indicate that the primary influence of temperature in the trunk is solar radiation and radiative energy from the soil and surrounding trees. Results from the summer simulation differed with previous results, indicating that sap flow in the trunk altered the internal temperature change with secondary effects attributed to the radiative energy from the soil and surrounding trees. Summer simulation results also showed that with sap flow, as the soil around the roots become unsaturated, the flow path for the roots will be changed to areas where the soil is still saturated with a corresponding increase in fluid velocity.

<p>Multiple Signals of Opportunity (multi-SoOp) across different frequencies and polarizations</p> <p>offer a potential breakthrough for remote sensing of root-zone soil moisture (RZSM). Deeper penetration depths of existing communication transmissions in the frequency ranges of 137–138, 240–270, and 360–380 MHz enable the estimation of RZSM by complementing global navigation satellite system reflectometry (GNSS-R) in L-band. The small form factor of the multi-SoOp observatory allows for high spatiotemporal coverage of RSZM by a satellite constellation in a cost-effective manner. This study aims to develop models and tools to define mission requirements for various system parameters that affect observation accuracy and coverage, for the advancement of spaceborne multi-SoOp remote sensing. These parameters include frequency and polarization combinations, observation error, inter-frequency temporal coincidence, and configuration of the satellite constellation. We present the development of a retrieval algorithm and the sensitivity analysis of retrieval accuracy. The retrieval algorithm was evaluated using synthetic observations generated from multiyear time series of in-situ soil moisture (SM) and satellite-based vegetation data. The combined use of both high and low frequencies improves retrieval accuracy by limiting uncertainties from vegetation and surface SM and providing sensitivity to deeper layers. A bivariate model, derived from the sensitivity analysis, facilitates error prediction for future science missions. We introduce a framework for tradespace exploration of the multi-SoOp satellite constellation. A constellation design study indicates that a Walker constellation comprising 24 satellites with 3 orbital planes at 500 km and 50° inclination optimizes the coverage and mission cost under mission requirements. A tower-based field experiment validated the performance of a prototype antenna for multi-SoOp using the interference pattern technique. More field experiments with improved instruments are required to further advance the multi-SoOp technique.</p>

Following wildfires, plant materials are direct-seeded to limit erosion and annual weed invasion. Seedlings often fail to establish because selected plant materials are not always well adapted to local soil moisture and temperature conditions. In an effort to help improve plant materials selection and to evaluate sites potential revegetation, we have worked toward developing methodology to predict germination and root growth based on site specific soil moisture and temperature conditions. First, we characterized the seedbed environment of 24 sagebrush (Artemisia spp.) steppe sites throughout the Intermountain West to determine the wet-thermal time of five temperature ranges relevant to germination response and thermal-time model accuracy (Chapter 1). Second, we predicted potential germination for 31 plant materials at those same sites (Chapter 2). Third, in preparation to predict root growth at multiple sites, we characterized the drying patterns and the associated plant-available water for in the seedling root zone across nine woodland (Juniperus spp. and Piñus spp.) sites (Chapter 3). For all of these studies, we determined the effects of tree reduction and tree infilling phase at time of tree reduction. Our key findings are that seedbeds generally sum most wet-thermal time at temperature ranges where the germination rates fit thermal accumulation models quite well (R2 ≥ 0.7). The majority of plant materials summed enough wet-thermal time for a potential germination at most sites during the fall, early spring, and late spring. Soil drying primarily occurs from the soil surface downward. Drying rates and Plant available water associated with the first drying event increased with increasing soil depth. Root zone (1-30 cm) plant-available water increased before and decreased after the first spring drying event with increasing soil depth. Tree removal with increasing pretreatment tree infilling phase generally added progress toward germination, plant available water, and wet-thermal time in the seedbed and root zones of the sagebrush steppe in the Great Basin. Because soil moisture and temperature does not appear to be limiting for potential germination, combining germination and root growth models to create a more comprehensive model may allow for a more robust prediction for seedling survival. For either root growth or combined germination and root growth models, plant available water and wet-thermal time before the first spring drying period hold the most potential for successfully predicting seedling survival.

This thesis is written as a cumulative dissertation based on peer-reviewed papers and supplemented by yet unpublished results. It presents methods and results that contribute to a novel approach for estimating water storage within the soil-water-plant system at a single site or in a small catchment (< 100 km2). The focus is on estimating the current/pre-event condition of a study area using simulated soil moisture and applying it as an indicator for flash flood forecasting. These two steps were combined in a semi-automatic framework that was used as a tool for flash flood monitoring after the Flash Flood Guidance (FFG) concept. This includes catchments for which Hydro-meteorological data and reliable site characteristics are not available. The overall objective was to demonstrate the capabilities and limitations of the regionally applicable modeling framework based on a lumped-physical model and open-source input data. The questions to be answered are: How reliable are the model outputs estimated by an uncalibrated-lumped model based on regional parameterization and forcing data? What are the potential uncertainties and limitations of such a framework? What are the potential applications of water storage in flood monitoring? The data were derived from freely available datasets. Meteorological input data can come from various sensor networks integrated in an open sensor web, mainly from the German Meteorological Service (DWD) and e.g., the forest climate stations of Sachsenforst. The model description required datasets for elevation (10 m, State Office for Environment, Agriculture and Geology-LfULG), land cover (Copernicus: Land Cover 100m), soil characteristics (BK50, LfULG) and soil profiles from the German National Forest Inventory (NFI). In addition, satellite-based soil moisture product (SMAP-L4-GPH from the National Aeronautics and Space Administration-NASA), water gauges data (LfULG) and eddy covariance flux cluster sites of the chair Meteorology at TU Dresden were used for validation. The first publication provides the framework and elaborates on the integration of a model into the open-data platform. The BROOK90 model (R version) was embedded in an open sensor web to estimate daily water balance components for more than 6,000 (sub-) catchments in Saxony. The model performance was validated with stream gauge observations in ten selected head catchments for discharge and with SMAP-L4-GPH for evapotranspiration and soil moisture. The results indicate that the framework is able to provide reliable soil retention estimates in high resolution. The second publication addresses the potential use of radar precipitation in this framework. Here the focus is on examining long-term radar-derived precipitation to improve water balance estimates due to its advantages in spatial coverage. The DWD’s re-analysis radar product, RADKLIM, was applied and aggregated for daily model input. A comparison between radar and rain gauge precipitation was performed to evaluate the quality of the product at the study sites, including the compensation for the catch loss in precipitation using the Richter correction. The results show the satisfactory performance of the framework with radar precipitation. The third publication demonstrates the application of model output to flood warnings. FFG was modified and applied to estimate rainfall thresholds considering the effects of antecedent soil moisture. Once rainfall threshold curves are calculated, only information on rainfall and soil moisture information is needed to issue a warning of a potential flash flood. The method was applied in the Wernersbach catchment in the Tharandt Forest and validated with historical events. The results of the contingency table show the potential of this tool for flash flood warning, but it should be tested with other rainfall runoff models and more catchments prone to flash floods.:Abstract/Zusammenfassung/Tóm tắt 1. Introduction 1.1 Motivation and scope 1.2 Problem formulation 1.3 Target setting 1.4 Structure of the thesis 2. Adjusted Flash Flood Guidance (FFG) framework 2.2 Terminology and definitions 2.2.1 Flash flood 2.2.2 Small catchment 2.3 FFG concept 2.4 Adjusted FFG framework 3. Core publications of the PhD thesis 4. Major findings 5. Conclusions and outlook References List of Abbreviations List of figures List of the author’s publication Appendixes including the core publications Erklärung / Die vorliegende Arbeit ist eine kumulative Dissertation, die auf begutachteten Arbeiten basiert und durch bisher unveröffentlichte Ergebnisse ergänzt wird. Sie stellt Methoden und Ergebnisse vor, die zu einem neuartigen Ansatz zur Abschätzung der Wasserspeicherung im System Boden-Wasser-Pflanze an einem einzelnen Standort oder in einem kleinen Einzugsgebiet (< 100 km2) beitragen. Der Schwerpunkt liegt auf der Abschätzung des aktuellen/vor einem Ereignis herrschenden Zustands eines Untersuchungsgebiets unter Verwendung simulierter Bodenfeuchte und deren Anwendung als Indikator für die Vorhersage von Sturzfluten. Diese beiden Schritte wurden in einem halbautomatischen Modell zusammengefasst, das als Werkzeug für die Überwachung von Sturzfluten nach dem Konzept des Flash Flood Guidance (FFG) verwendet wird. Dies schließt Standorte/Einzugsgebiete ein, für die keine hydrometeorologischen Daten und/oder zuverlässige Standortmerkmale verfügbar sind. Das Gesamtziel bestand darin, die Fähigkeiten und Grenzen des regional anwendbaren Modells auf der Grundlage eines pauschalen physikalischen Modells und von Open-Source-Eingangsdaten zu demonstrieren. Die zu beantwortenden Fragen lauten: Wie zuverlässig sind die von einem unkalibrierten eindimensionalen Modell auf der Grundlage regionaler Parametrisierungs- und Antriebsdaten geschätzten Modellergebnisse? Was sind die potenziellen Unsicherheiten und Grenzen eines solchen Modells? Welches sind die möglichen Anwendungen der simulierten Komponenten des Wasserhaushalts bei der Überwachung von Hochwasser? Die Daten werden aus frei verfügbaren Datensätzen abgeleitet. Die meteorologischen Eingangsdaten stammen aus verschiedenen Sensornetzwerken, die in einem Open Sensor Web integriert sind, hauptsächlich vom Deutschen Wetterdienst (DWD) und z.B. den Waldklimastationen von Sachsenforst. Für die Modellbeschreibung wurden Datensätze für Geländehöhe (10 m, Landesamt für Umwelt, Landwirtschaft und Geologie - LfULG), Landbedeckung (Copernicus: Land Cover 100m), Bodeneigenschaften (BK50, LfULG) und Bodenprofile aus der Bundeswaldinventur (BWI) benötigt. Darüber hinaus werden satellitengestützte Bodenfeuchteprodukte (SMAP-L4-GPH der National Aeronautics and Space Administration-NASA), Pegeldaten (LfULG) und Eddy-Kovarianz-Flusscluster-Standorte des Lehrstuhls für Meteorologie der TU Dresden zur Validierung verwendet. Die erste Veröffentlichung liefert den Rahmen und erläutert die Integration eines Modells in die offene Datenplattform. Das Modell BROOK90 (R-Version) wurde in ein offenes Sensornetz eingebettet, um tägliche Wasserhaushaltskomponenten für mehr als 6,000 (Teil-)Einzugsgebiete in Sachsen zu schätzen. Die Leistung des Modells wurde anhand von Pegelbeobachtungen in zehn ausgewählten Einzugsgebieten für den Abfluss und mit SMAP-L4-GPH für die Evapotranspiration und Bodenfeuchte validiert. Die Ergebnisse zeigen, dass das System in der Lage ist, zuverlässige Schätzungen der Bodenretention in hoher Auflösung zu liefern. Die zweite Veröffentlichung befasst sich mit der möglichen Nutzung von Radarniederschlägen in diesem Rahmen. Hier liegt der Schwerpunkt auf der Untersuchung des langfristigen, vom Radar abgeleiteten Niederschlags zur Verbesserung der Wasserbilanzschätzungen aufgrund seiner Vorteile bei der räumlichen Abdeckung. Das Reanalyse-Radarprodukt des DWD, RADKLIM, wurde verwendet und für tägliche Modelleingaben aggregiert. Es wurde ein Vergleich zwischen Radar- und Regenmesser-Niederschlag durchgeführt, um die Qualität des Produkts an den Untersuchungsstandorten zu bewerten, einschließlich der Kompensation des Niederschlagsverlusts durch die Richter-Korrektur. Die Ergebnisse zeigen die zufriedenstellende Leistung des Rahmens mit Radarniederschlag. Die dritte Veröffentlichung demonstriert die Anwendung der Modelldaten auf Hochwasserwarnungen. Der Leitfaden für Sturzflutwarnungen wurde modifiziert und zur Schätzung der Niederschlagsschwellen unter Berücksichtigung der Auswirkungen der vorherrschenden Bodenfeuchte angewandt. Sobald die Niederschlagsschwellenkurven berechnet sind, werden nur noch Informationen über Niederschlag und Bodenfeuchte benötigt, um eine Warnung vor einer möglichen Sturzflut auszusprechen. Die Methode wurde im Einzugsgebiet des Wernersbachs und im Tharandter Wald angewandt und mit historischen Ereignissen validiert. Die Ergebnisse der Kontingenztabelle zeigen das Potenzial dieses Werkzeugs für die Sturzflutwarnung, es sollte jedoch mit anderen Niederschlagsabflussmodellen und weiteren Einzugsgebieten, die für Sturzfluten anfällig sind, getestet werden.:Abstract/Zusammenfassung/Tóm tắt 1. Introduction 1.1 Motivation and scope 1.2 Problem formulation 1.3 Target setting 1.4 Structure of the thesis 2. Adjusted Flash Flood Guidance (FFG) framework 2.2 Terminology and definitions 2.2.1 Flash flood 2.2.2 Small catchment 2.3 FFG concept 2.4 Adjusted FFG framework 3. Core publications of the PhD thesis 4. Major findings 5. Conclusions and outlook References List of Abbreviations List of figures List of the author’s publication Appendixes including the core publications Erklärung / Luận án tiến sĩ này được viết như một luận án tích lũy dựa trên các bài báo đã được bình duyệt và được bổ sung bởi các kết quả chưa được công bố. Nó trình bày các phương pháp và kết quả góp phần vào một cách tiếp cận mới để ước tính trữ lượng nước trong hệ thống đất-nước- thực vật tại một địa điểm hoặc trong một lưu vực nhỏ (<100 km2). Trọng tâm là ước tính tình trạng hiện tại / trước sự kiện của khu vực nghiên cứu bằng cách sử dụng độ ẩm đất mô phỏng và áp dụng nó như một chỉ báo để dự báo lũ quét. Hai bước này được kết hợp trong một khuôn khổ bán tự động được sử dụng như một công cụ để giám sát lũ quét dựa theo khái niệm Hướng dẫn về lũ quét (FFG). Điều này bao gồm các địa điểm / lưu vực không có sẵn dữ liệu khí tượng thủy văn và / hoặc các đặc điểm thiếu thông tin mô tả chia tiết đáng tin cậy. Mục tiêu tổng thể là chứng minh các khả năng và hạn chế của khung mô hình áp dụng trong khu vực dựa trên một mô hình vật lý tổng hợp và dữ liệu đầu vào nguồn mở. Các câu hỏi cần được trả lời là: Các kết quả đầu ra của mô hình được ước tính bằng một mô hình gộp chưa hiệu chỉnh dựa trên tham số vùng và dữ liệu đáng tin cậy đến mức nào? Những điểm không chắc chắn và hạn chế tiềm ẩn của một khuôn khổ như vậy là gì? Các ứng dụng tiềm năng của thành phần cân bằng nước mô phỏng trong giám sát lũ lụt là gì? Dữ liệu được lấy từ các bộ dữ liệu miễn phí và có sẵn. Dữ liệu đầu vào về khí tượng đến từ các mạng cảm biến khác nhau được tích hợp trong một Open Sensor Web, chủ yếu từ Cơ quan Khí tượng Đức (DWD) và các trạm khí hậu rừng của Sachsenforst. Mô tả mô hình yêu cầu bộ dữ liệu về độ cao (10 m, Văn phòng bang về Môi trường, Nông nghiệp và Địa chất-LfULG), lớp phủ đất (Copernicus: Land Cover 100m), đặc điểm của đất (BK50, LfULG) và cấu hình đất từ Kiểm kê Rừng Quốc gia Đức (NFI). Ngoài ra, sản phẩm độ ẩm của đất dựa trên vệ tinh (SMAP-L4-GPH từ Cơ quan Hàng không và Vũ trụ Quốc gia-NASA), dữ liệu các trạm thủy văn (LfULG) và các cụm địa điểm eddy covariance được giám sát bởi khoa Khí tượng học tại TU Dresden được sử dụng để xác nhận kết quả mô hình đầu ra. Ấn phẩm đầu tiên cung cấp khuôn khổ và trình bày chi tiết về việc tích hợp một mô hình vào nền tảng dữ liệu mở. Mô hình BROOK90 (phiên bản R) được nhúng vào một trang web cảm biến mở để ước tính các thành phần cân bằng nước hàng ngày cho hơn 6000 lưu vực (phụ) ở Sachsen. Hiệu suất của mô hình đã được xác nhận với các quan sát bằng dữ liệu dòng chảy ở mười lưu vực đầu nguồn được chọn và với SMAP-L4-GPH cho thành phần thoát hơi nước và độ ẩm của đất. Kết quả chỉ ra rằng khung có thể cung cấp các ước tính đáng tin cậy về khả năng giữ nước của đất ở độ phân giải cao. Ấn phẩm thứ hai đề cập đến khả năng sử dụng lượng mưa radar trong khuôn khổ này. Ở đây, trọng tâm là kiểm tra lượng mưa dài hạn có nguồn gốc từ radar để cải thiện ước tính cân bằng nước do lợi thế của nó trong phạm vi bao phủ không gian. Sản phẩm radar phân tích lại của DWD, RADKLIM, đã được áp dụng và tổng hợp để nhập mô hình hàng ngày. So sánh giữa lượng mưa bằng radar và máy đo mưa đã được thực hiện để đánh giá chất lượng của sản phẩm tại các điểm nghiên cứu, bao gồm cả việc bù đắp cho lượng mưa thất thoát bằng cách sử dụng hiệu chỉnh độ Richter. Kết quả cho thấy hiệu suất khả quan của khung với lượng mưa radar. Ấn phẩm thứ ba trình bày việc áp dụng đầu ra mô hình để cảnh báo lũ lụt. Hướng dẫn về lũ quét đã được sửa đổi và áp dụng để ước tính ngưỡng lượng mưa xem xét ảnh hưởng của độ ẩm đất trước đây. Khi đường cong ngưỡng mưa được tính toán, chỉ cần thông tin về lượng mưa và thông tin về độ ẩm của đất để đưa ra cảnh báo về khả năng xảy ra lũ quét. Phương pháp này đã được áp dụng ở lưu vực Wernersbach, trong Rừng Tharandt và được xác nhận với các sự kiện lịch sử. Kết quả của bảng dự phòng cho thấy tiềm năng của công cụ này để cảnh báo lũ quét, nhưng nó nên được thử nghiệm với các mô hình dòng chảy lượng mưa khác và các lưu vực dễ xảy ra lũ quét hơn.:Abstract/Zusammenfassung/Tóm tắt 1. Introduction 1.1 Motivation and scope 1.2 Problem formulation 1.3 Target setting 1.4 Structure of the thesis 2. Adjusted Flash Flood Guidance (FFG) framework 2.2 Terminology and definitions 2.2.1 Flash flood 2.2.2 Small catchment 2.3 FFG concept 2.4 Adjusted FFG framework 3. Core publications of the PhD thesis 4. Major findings 5. Conclusions and outlook References List of Abbreviations List of figures List of the author’s publication Appendixes including the core publications Erklärung

Measuring soil moisture content (SMC) in mining waste rock is important for assessing and modelling hydrological processes which influence pollutant release. Here, an experimental setup containing mining waste rock is established to compare the performance of 4 Arduino capacitance moisture sensors to one single Time Domain Reflectometry (TDR) sensor. Furthermore, the performance of these sensors is evaluated in both sieved and unsieved mining waste rock. Fitted calibration curves are provided for both the TDR- and Arduino-sensors individually and in combination. These calibration curves are evaluated using the RMSE and R 2 of each curve and compared between sensors and soil texture. It is concluded that using more capacitance sensors significantly improves the fit statistics of the calibration curves and that using at least 4 capacitance sensors can enhance calibration curve fitting. For both the TDR and capacitance sensors, the calibration curves in sieved soil provided the best fit, meaning that soil specific calibration of sensors is recommended. On a sensor individual basis, the temporal precision of the TDR sensor was superior to each individual capacitance sensor. Use of 4 or more Arduino capacitance sensors may especially be justified in circumstances where the spatial variability of SMC is addressed by executing a large number of measurements. Here, the feasibility of the Arduino sensor system means that the use of these low-cost sensors, despite their reduced temporal precision, can be upscaled at relatively small costs.

Elevated concentrations of nutrients, particularly nitrate, in groundwater and springs in Florida are a growing resource management concern. Stormwater infiltration basins, which are a common stormwater management practice in the well-drained karst terrain areas of Florida, are a potentially important source of nutrients to the groundwater system because stormwater exits the basin by only evaporation or infiltration. To better understand the biogeochemical processes integrating stormwater infiltration impacts on groundwater resources in a field-scale setting, a combination of hydrologic, soil chemistry, water chemistry, dissolved and soil gas, isotope, and microbiological data was collected from 2007 through 2010 at two stormwater infiltration basins receiving runoff from predominantly residential watersheds in north-central Florida. Substantially different biogeochemical processes affecting nitrogen fate and transport were observed beneath the two stormwater infiltration basins. Differences are related to soil textural properties that deeply link hydroclimatic conditions with soil moisture variations in a humid, subtropical climate. During 2008, shallow groundwater beneath the basin with predominantly clayey soils (median 41% silt+clay content) exhibited decreases in dissolved oxygen from 3.8 to 0.1 mg/L and decreases in nitrate-nitrogen from 2.7 mg/L to less than 0.016 mg/L, followed by manganese and iron reduction, sulfate reduction, and methanogenesis. In contrast, beneath the basin with predominantly sandy soils (median 2% silt+clay content), aerobic conditions persisted from 2007 through 2009 (dissolved oxygen of 5.0â€"7.8 mg/L), resulting in nitrate-nitrogen of 1.3â€"3.3 mg/L in shallow groundwater. Soil extractable nitrate-nitrogen was significantly lower and the copper-containing nitrite reductase gene density was significantly higher beneath the clayey basin. Differences in moisture retention capacity between fine- and coarse-textured soils resulted in median volumetric gas-phase contents of 0.04 beneath the clayey basin and 0.19 beneath the sandy basin, inhibiting surface/subsurface oxygen exchange beneath the clayey basin. Subsurface biogeochemical processes at the clayey stormwater infiltration basin were further analyzed to better understand the effects of the highly variable hydrologic conditions common in humid, subtropical climates. Cyclic variations in biogeochemical processes generally coincided with wet and dry hydroclimatic conditions. Oxidizing conditions in the subsurface persisted for about one month or less at the beginning of wet periods with dissolved oxygen and nitrate showing similar temporal patterns. Reducing conditions in the subsurface evolved during prolonged flooding of the basin. At about the same time oxygen and nitrate reduction concluded, manganese, iron, and sulfate reduction began, with the onset of methanogenesis one month later. Reducing conditions persisted up to six months, continuing into subsequent dry periods until the next major oxidizing infiltration event. Evidence of denitrification in shallow groundwater at the site is supported by median nitrate-nitrogen less than 0.016 mg/L, excess nitrogen gas up to 3 mg/L progressively enriched in delta-15N during prolonged basin flooding, and isotopically heavy delta-15N and delta-18O of nitrate (up to 25 and 15 per mil, respectively). Isotopic enrichment of newly infiltrated stormwater suggests denitrification was partially completed within two days. Soil and water chemistry data suggest a biogeochemically active zone exists in the upper 1.4 m of soil, where organic carbon was the likely electron donor supplied by organic matter in soil solids or dissolved in infiltrating stormwater. The cyclic nature of reducing conditions effectively controlled the nitrogen cycle, switching nitrogen fate beneath the basin from nitrate leaching to reduction in the shallow saturated zone. Soil beneath the sandy stormwater infiltration basin was amended using biosorption activated media (BAM) to study the effectiveness of this technology in reducing inputs of nitrogen and phosphorus to groundwater. The functionalized soil amendment BAM consists of a 1.0:1.9:4.1 mixture (by volume) of tire crumb (to increase sorption capacity), silt and clay (to increase soil moisture retention), and sand (to promote sufficient infiltration), which was applied to develop an innovative best management practice (BMP) utilizing nutrient reduction and flood control sub-basins. Construction and materials costs, excluding profit and permit fees, for the innovative BMP were about $US 65 per square meter of basin bottom. Comparison of nitrate/chloride ratios for the shallow groundwater indicate that prior to using BAM, nitrate concentrations were substantially influenced by nitrification or variations in nitrate input. In contrast, for the new basin utilizing BAM, nitrate/chloride ratios indicate minor nitrification and nitrate losses with the exception of one summer sample that indicated a 45% loss. Biogeochemical indicators (denitrifier activity derived from real-time polymerase chain reaction and variations in major ions, nutrients, dissolved and soil gases, and stable isotopes) suggest nitrate losses are primarily attributable to denitrification, whereas dissimilatory nitrate reduction to ammonium and plant uptake are minor processes. Denitrification was likely occurring intermittently in anoxic microsites in the unsaturated zone, which was enhanced by increased soil moisture within the BAM layer and resultant reductions in surface/subsurface oxygen exchange that produced conditions conducive to increased denitrifier activity. Concentrations of total dissolved phosphorus and orthophosphate were reduced by more than 70% in unsaturated zone soil water, with the largest decreases in the BAM layer where sorption was the most likely mechanism for removal. Post-BAM orthophosphate/chloride ratios for shallow groundwater indicate predominantly minor increases and decreases in orthophosphate with the exception of one summer sample that indicated a 50% loss. Differences in nutrient variations between the unsaturated zone and shallow groundwater may be the result of the intensity and duration of nutrient removal processes and mixing ratios with water that had undergone little biogeochemical transformation. In order to quantify potential processes leading to observed nitrogen losses beneath the innovative BMP, an integrated infiltration basinâ€"nitrogen reduction (IBNR) system dynamics model was developed. Based on two simulation periods, the IBNR model indicated denitrification accounted for a loss of about one-third of the total dissolved nitrogen mass inflow and was occurring predominantly in the BAM layer. The IBNR model results in combination with the field-based biogeochemical assessment demonstrated that the innovative BMP using the functionalized soil amendment BAM is a promising passive, economical, stormwater nutrient-treatment technology. Further field- and laboratory-scale research on the long-term sustainability of nutrient losses and further elucidation of causative physicochemical and biogeochemical mechanisms would contribute to improved BAM performance and green infrastructure development in the future.